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After the migration of metadata to Kylin4, let's share the qualitative changes and substantial performance improvements brought about by some of the promising scenarios. First of all, in a scenario like Commodity Insight, there is a large store of hundreds of thousands of commodities with several hundred thousand of commodities. We have to analyze its transactions and traffic, etc. There are more than a dozen precise precisely count distinct measures in single cube. Precisely count distinct measure is actually very inefficient if it is not optimized through pre-calculation and Bitmap. Kylin currently uses Bitmap to support precisely count distinct measure. In a scene that requires complex queries to sort hundreds of thousands of commodities in various UV(precisely count distinct measure), the RT of Kylin 2 is 27 seconds, while the RT of Kylin 4 is reduced from 27 seconds to less than 2 seconds.

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